Experts Advocate Collaborations to Harness AI in Medical Education

Advancements in artificial intelligence (AI) are poised to revolutionize medical education, according to a new study published in The Lancet Digital Health. Researchers from Duke-NUS Medical School, Singapore General Hospital, and Tsinghua University emphasize the necessity for stronger collaborations among medical schools, hospitals, and regulatory bodies to ensure the safe and effective integration of AI in training future healthcare professionals. The study highlights significant barriers to AI adoption, including ethical concerns and limited resources, which must be addressed to fully unlock its potential.

As global healthcare systems grapple with staffing shortages and increasing demands for high-quality care, the World Health Organization (WHO) projects a shortfall of approximately 10 million healthcare workers by 2030. In this context, the implementation of AI tools could facilitate the training of medical students and professionals more efficiently, ultimately benefiting patient care.

AI Enhancements in Medical Training

The study outlines how AI-powered tools can create immersive learning experiences, enabling medical students to engage with virtual patients and practice procedural skills in metaverse environments. These AI systems, including large language models (LLMs) like ChatGPT, can personalize educational experiences and simulate complex clinical scenarios, offering consistency and versatility without significant logistical or financial limitations.

Dr. Jasmine Ong, a joint first author of the paper, emphasizes that AI is designed to complement, not replace, clinical educators. “AI enables educators and mentors to focus on what matters most—fostering meaningful connections with their learners,” she stated. By acting as a digital co-tutor, AI can provide personalized feedback and realistic clinical simulations, shaping the next generation of healthcare professionals.

Addressing Challenges and Ethical Considerations

Despite the promising applications of AI, challenges remain in its integration into medical education. The research identifies a shortage of qualified trainers and a lack of proven implementation strategies as major obstacles. Concerns regarding the accuracy of LLMs, including instances of fabricated information or “hallucinations,” pose risks to their credibility. Moreover, biases related to gender and race in AI outputs could perpetuate systemic disparities within medical training.

Dr. Ning Yilin, another joint first author, highlights the importance of addressing ethical issues as AI becomes more entrenched in medical education. “We need to ensure appropriate use, maintain learning integrity, and prevent unintended harms,” he said. This necessitates comprehensive guidelines and responsible design principles.

The researchers advocate for a collaborative approach across multiple sectors, including healthcare institutions, medical schools, industry partners, and government bodies. Associate Professor Liu Nan, director of the Duke-NUS AI + Medical Sciences Initiative, stresses that a global strategy is essential for deploying AI responsibly. “By working towards comprehensive partnerships, we can create more interactive and accessible training that translates into better patient care,” he noted.

The study calls for the development of practical frameworks and funding models to facilitate the sustainable adoption of AI in medical education. Such collaborations are vital to establishing resource supports that can enhance training programs and ultimately improve healthcare outcomes.

For further reading, refer to the study by Yilin Ning et al., “How can artificial intelligence transform the training of medical students and physicians?” published in The Lancet Digital Health in 2025.